Sales Data Engineer

onsemiKuala Selangor, SelangorOn-siteFull-timeMid level, 2–5 yearsListed 6 hours ago

Apply now

About this role

We are seeking a Data Engineer to support Sales Data and Analytics initiatives by designing, maintaining, and enhancing critical data pipelines and data flows. This role will be responsible for building scalable data solutions, troubleshooting and resolving data issues, improving existing Snowflake/SQL server data architectures, and ensuring reliable delivery of sales-related data across reporting and analytics platforms.

The ideal candidate will partner closely with Sales Operations, IT, and Analytics teams to identify data challenges, optimize data processes, and accelerate the resolution of sales data issues. By strengthening data quality, performance, and automation, this role will help create a more agile and reliable sales data ecosystem, reducing time to resolution for data issues/enhancements, and enabling the sales organization to access accurate, timely, and actionable information for decision making.

Experience

- 4–7 years of experience in Data Engineering, Database Development, or related roles.

- Solid hands-on experience with different database technologies ( Snowflake , Microsoft SQL Server) .

- Proven experience using DBT for data transformation and modeling. Experience in designing and supporting enterprise-scale data pipelines and data warehouse solutions.

- Experience with GitLab and version control best practices.

- Mid to Expert-level SQL development skills with ability to write clean, efficient, and maintainable code.

- Solid understanding of ETL/ELT frameworks and modern data architecture.

Soft Skills

- Strong analytical and problem-solving skills.

- Ability to work independently with minimal supervision.

- Excellent troubleshooting and diagnostic capabilities.

- Proactive mindset with a focus on continuous improvement.

- Strong communication and stakeholder management skills.

- Ability to propose and drive innovative solutions that improve performance, scalability, and operational efficiency.